code: def _create_dino_linear_eval_config(
      checkpoint_path: str, gpu_count: int = 2
  ):
      cfg = compose_hydra_configuration(
          [
              "config=test/integration_test/quick_eval_in1k_linear",
              "+config/benchmark/linear_image_classification/imagenet1k/models=dino_xcit_s16",
              f"config.MODEL.WEIGHTS_INIT.PARAMS_FILE={checkpoint_path}",
              f"config.DISTRIBUTED.NUM_PROC_PER_NODE={gpu_count}",
              # Datasets
              "config.DATA.TRAIN.DATA_SOURCES=[synthetic]",
              "config.DATA.TRAIN.LABEL_SOURCES=[synthetic]",
              "config.DATA.TRAIN.BATCHSIZE_PER_REPLICA=4",
              "config.DATA.TRAIN.RANDOM_SYNTHETIC_IMAGES=True",
              "config.DATA.TRAIN.DATA_LIMIT=32",
              "config.DATA.TRAIN.USE_DEBUGGING_SAMPLER=True",
              "config.DATA.TEST.DATA_SOURCES=[synthetic]",
              "config.DATA.TEST.LABEL_SOURCES=[synthetic]",
              "config.DATA.TEST.BATCHSIZE_PER_REPLICA=4",
              "config.DATA.TEST.RANDOM_SYNTHETIC_IMAGES=True",
              "config.DATA.TEST.DATA_LIMIT=32",
              "config.DATA.TEST.USE_DEBUGGING_SAMPLER=True",
              # To get the logs reliably
              "config.LOG_FREQUENCY=1",
              "config.REPRODUCIBILITY.CUDDN_DETERMINISTIC=True",
              "config.OPTIMIZER.num_epochs=2",
          ]
      )
      args, config = convert_to_attrdict(cfg)
      return config
  
file_path: vissl/tests/test_dino_xcit.py
imports: import os
  import unittest
  from vissl.utils.hydra_config import compose_hydra_configuration, convert_to_attrdict
  from vissl.utils.test_utils import gpu_test, in_temporary_directory, run_integration_test
label_desc: Use image node_id 2 for calling the TestDINO_XCIT obj's underlying member method code with example usage: obj._create_dino_linear_eval_config(checkpoint_path, gpu_count) and returns: config